2.6 Statistical analysis
Descriptive data are reported as the median with interquartile ranges
for continuous data and numbers with percentages for categorical data.
To assess the association between baloxavir use and those outcomes, we
used univariate and multivariable logistic regression analyses adjusting
for demographic data (age and sex) and comorbid conditions (five
categories).
We conducted a prespecified subgroup analysis. Baloxavir was compared
with each NAI. This analysis was planned since laninamivir is thus far
licensed exclusively in Japan [17]. For this analysis, only
risk-adjusted odds ratio (aOR) was reported. We also planned a subgroup
analysis stratified by virus type, but influenza type B infection was
only infrequently found in our data set (<1%); consequently,
we did not perform this subgroup analysis.
A P value <0.05 was considered statistically
significant. P value adjustment for multiple comparisons was not
conducted, and thus the findings for secondary outcomes and subgroup
analysis should be viewed as exploratory, hypothesis-generating testing
[18]. All analyses were done with R statistical environment
(https://cran.r-project.org/), under version 3.61.